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    This study introduces a novel infrared polarization imaging method to suppress star-like clutter on water surfaces. The technique significantly enhances signal-to-clutter ratio while preserving target details for improved detection.

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    Area of Science:

    • Optics and Photonics
    • Signal Processing
    • Remote Sensing

    Background:

    • Star-like clutter on water surfaces poses a significant challenge for target detection in infrared imaging.
    • Existing clutter suppression methods often struggle to balance suppression effectiveness with target information preservation.

    Purpose of the Study:

    • To develop and evaluate a novel clutter suppression method for infrared images of water surfaces.
    • To enhance the signal-to-clutter ratio (SCR) and preserve target details for improved target detection and recognition.

    Main Methods:

    • Utilized infrared polarization imaging technology for global clutter suppression.
    • Employed the Reed-Xiaoli anomaly detection algorithm to identify remaining clutter.
    • Applied an image filtering algorithm for further clutter reduction.

    Main Results:

    • Achieved a signal-to-clutter ratio improvement of up to 152%.
    • Effectively preserved target information and background texture features.
    • Demonstrated superior performance compared to existing clutter suppression algorithms.

    Conclusions:

    • The proposed infrared polarization-based method offers a robust solution for clutter suppression on water surfaces.
    • Effective clutter suppression and target detail preservation significantly enhance scene understanding for target detection and recognition.